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Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
TqSdk
86 documents
Quantpedia
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Binance API docs
45 documents
Quantopian lectures
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

22,592 documents

SuperMind

This stock-screening idea combines metaverse-sector membership, an arc-shaped price pattern, and daily MACD above zero. The document then expands the proposed conditions with Bollinger Band width below three and a 20-day volatility measure below ten. Its…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The document proposes screening Chinese A-share stocks for a daily high-low range greater than one percent of the prior close, positive large-order net volume, and ranking by the day’s auction turnover to select the top five. It frames these conditions as a…

EquitiesChina marketsMarket microstructureBacktesting
SuperMind

The document describes a Chinese stock screen combining turnover between 3% and 12%, an appearance on the previous day's trading leaderboard, positive trailing price-to-earnings ratio, and a listing-age condition of more than one year. The stated intent is…

EquitiesChina marketsStatisticsRisk management
SuperMind

The document describes a Chinese equity screen requiring a relative strength index below 65, a daily gain above 1%, main-board listing, a robotics concept classification, and circulating market value below 10 billion yuan. It combines a momentum condition…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This post presents a simple Chinese equity screening rule based on daily price range and turnover, while excluding stocks from the STAR Market. The intended rationale is to find shares with both price movement and trading activity, potentially suitable for…

EquitiesTechnical indicatorsExecutionRisk management
BigQuant

The study examines timing the basis between Chinese equity indices and their futures, motivated by persistent futures discounts and uncertainty for market-neutral funds. To reduce the influence of carry components such as rates, dividends, and time to…

FuturesEquitiesMean reversionMomentum
SuperMind

The document describes a Chinese equity screen for Shenzhen Main Board stocks. It selects stocks with amplitude above 1, price-to-earnings ratios from 0 to 29.01, price-to-book ratios from 0 to 3.11, and 10-day returns above 0 but below 35. The author frames…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock-selection rule screens for turnover between 3% and 12%, a rising K value from the KDJ indicator, and a daily price change bounded around the previous close. The article describes these as technical and market-activity filters intended to identify…

EquitiesTechnical indicatorsMomentumStatistics
SuperMind

This stock screen selects companies in the metaverse theme whose institutional-flow measure is above zero and whose 14-period RSI is below 65. The stated rationale combines exposure to a popular sector with a positive institutional signal and a momentum…

EquitiesTechnical indicatorsMomentumRisk management
BigQuant

This research note studies whether stocks featured on China’s daily price-change leaderboards attract investor attention and how that attention relates to later returns. Using Sogou search index data as an attention proxy, it reports a U-shaped relationship…

EquitiesChina marketsMomentumFactor investing
SuperMind

This short-term stock screen targets A-share companies in the metaverse sector that appeared on the Dragon-Tiger trading list the previous day and had a volume ratio between 1.5 and 6. The document presents the conditions as a way to find stocks with…

EquitiesChina marketsTechnical indicatorsRisk management
BigQuant

The document answers a brief question about counting stocks within each industry group in a quantitative data expression. Its example groups records by the first-level Shenwan industry field and sums a conditional value: one for rows whose amount is…

EquitiesStatisticsChina markets
SuperMind

The document describes an equity screen combining a 14-period RSI below 65, three consecutive down days, and the prior day’s actual turnover between 3% and 28%. It presents these filters as a way to find stocks after a short decline while retaining a minimum…

EquitiesTechnical indicatorsMean reversionChina markets
SuperMind

This Chinese A-share screening proposal looks for stocks with daily MACD above zero and weekly MACD above zero, then ranks eligible names by a market-attention measure. The selection is intended to run after the weekly close. Its accompanying example…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This proposed Chinese A-share screen selects companies in the metaverse industry with a circulating share count no greater than 5.5 billion and a positive institutional net-buy rate over the previous month. The article describes institutional buying as a…

China marketsEquitiesSentiment
SuperMind

This A-share screening idea combines price movement, a short-term reversal pattern, and institutional ownership. It describes filtering for an amplitude threshold above 1, a Morning Star-like signal, and evidence of institutional buying. The indicator…

EquitiesTechnical indicatorsVolatilityChina markets
SuperMind

This A-share stock screen combines daily turnover, a rising DEA signal, and circulating market capitalization. It seeks stocks with turnover between 3% and 12%, capitalization between 5 billion and 10 billion yuan, and an upward-moving DEA measure. The…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This post proposes a Chinese stock screen combining membership in the metaverse theme, an upward-moving 30-day moving average, and a rounded price pattern. It presents the pattern as a way to describe recent price structure and includes sample indicator…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This post describes a Chinese A-share stock screen using a turnover-rate range of 3% to 12%, excluding Beijing-listed shares, and requiring at least two limit-up days within the previous 500 trading days. It frames limit-up events as a possible signal of…

China marketsEquitiesSentimentTechnical indicators
SuperMind

This Chinese-market stock screen combines price movement, company profitability, market capitalization, and opening-auction buying activity. It selects shares with amplitude above 1, market capitalization within the stated 10-billion limit, positive net…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This stock-selection rule combines three filters: amplitude above 1, a daily maximum decline between 4% and 5%, and a daily MACD value above zero. The stated rationale is to look for shares with notable price movement that have also retained a positive…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This Chinese stock-screening proposal combines a minimum daily amplitude, three consecutive limit-up closes on the previous day, and evidence of a limit-up within the prior 25 trading days. The refined criteria raise the amplitude threshold to 1.5% and…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This Chinese A-share screening idea combines membership in a metaverse-related category, a positive return, and a money-flow strength ranking. The article’s final version adds a positive market-capitalization condition. Its example formula compares a 21-day…

EquitiesChina marketsTechnical indicatorsRisk management